senior data engineer

business analyst

data scientist

it support engineer

service desk engineer

data engineer

AlphaBOLD

<div><div>Lahore, Pakistan (On-site/Hybrid)
</div><div>Posted: April 14, 2026</div></div>
 <div><h2 class="jobSectionHeader">Job Summary</h2>

Alphabold is looking for a skilled Data Engineer with 3&ndash;5 years of experience to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate will have strong expertise in data processing, database systems, and cloud platforms, enabling efficient data flow and analytics across the organization.
<h3 class="jobSectionHeader">
Key Responsibilities</h3>
<ul><li>Design, develop, and maintain scalable ETL/ELT data pipelines</li>
<li>Build and optimize data architectures, data lakes, and data warehouses</li>
<li>Ensure data quality, integrity, and reliability across systems</li>
<li>Collaborate with data analysts, data scientists, and business stakeholders to deliver data solutions</li>
<li>Develop and manage batch and real-time data processing systems</li>
<li>Monitor and troubleshoot data pipeline performance and failures</li>
<li>Implement data governance, security, and compliance best practices</li>
<li>Automate workflows and improve data engineering processes</li>
</ul><h3 class="jobSectionHeader">Required Skills &amp; Qualifications</h3>
<ul><li>3&ndash;5 years of experience in data engineering or related roles</li>
<li>Strong proficiency in SQL and Python (or Scala/Java)</li>
<li>Hands-on experience with ETL tools and frameworks (e.g., Apache Airflow, Talend, Informatica)</li>
<li>Experience with big data technologies such as Apache Spark, Hadoop, or Kafka</li>
<li>Solid understanding of data warehousing concepts and modeling (Star/Snowflake schema)</li>
<li>Experience with cloud platforms like AWS, Azure, or Google Cloud</li>
<li>Familiarity with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB)</li>
<li>Experience with version control systems (e.g., Git)</li>
</ul><h3 class="jobSectionHeader">Preferred Qualifications</h3>
<ul><li>Experience with containerization tools like Docker and orchestration tools like Kubernetes</li>
<li>Knowledge of CI/CD pipelines and DevOps practices</li>
<li>Familiarity with data visualization tools (e.g., Power BI, Tableau)</li>
<li>Understanding of streaming data systems and real-time analytics</li>
</ul><h3 class="jobSectionHeader">Soft Skills</h3>
<ul><li>Strong problem-solving and analytical skills</li>
<li>Good communication and collaboration abilities</li>
<li>Ability to work in a fast-paced, agile environment</li>
<li>Attention to detail and commitment to data accuracy</li>
</ul><h3 class="jobSectionHeader">Education</h3>
<ul><li>Bachelor&rsquo;s degree in Computer Science, Engineering, Information Technology, or a related field</li>
</ul><h3 class="jobSectionHeader">Nice to Have</h3>
<ul><li>Certifications in cloud platforms (AWS, Azure, GCP)</li>
<li>Experience working with large-scale distributed systems</li></ul></div>

Data Engineer

H2o Labs

Senior / Lead / Data Engineer &ndash; Comprehensive Job DescriptionAbout the RoleWe are seeking a highly skilled and experienced Senior/Lead/Staff Data Engineer todesign, build, and maintain scalable, reliable, and high-performance data systems. Thisrole requires deep technical expertise, strong ownership of data platforms, and the abilityto lead cross-functional initiatives that power analytics, machine learning, businessintelligence, and mission-critical applications.You will play a key role in shaping data architecture, ensuring data quality and governance,and enabling teams across the organization to make data-driven decisions withconfidence.Key ResponsibilitiesData Architecture &amp; Modeling<ul><li>Design and implement scalable data models, including:</li></ul>o Star schema (fact and dimension tables)o Conceptual, logical, and physical data models<ul><li>Develop enterprise data warehouse solutions ensuring:</li></ul>o Flexibility, scalability, and performance optimization<ul><li>Define and enforce data modeling standards and best practices</li></ul>Data Engineering &amp; Pipeline Development<ul><li>Build and maintain end-to-end data pipelines:</li></ul>o Data ingestion &rarr; staging &rarr; transformation &rarr; serving layers<ul><li>Develop robust ETL/ELT processes using modern tools and frameworks</li><li>Implement:</li></ul>o Typed staging layerso Data validation pipelineso Safe backfill and replay mechanisms<ul><li>Optimize SQL queries, indexing strategies, and database performanceData Platform Reliability &amp; Observability</li><li>Own data pipeline reliability and integrity</li><li>Build observability systems, including:</li></ul>o Monitoring dashboardso Alerting frameworks (actionable, low-noise)o Data freshness tracking<ul><li>Implement:</li></ul>o Schema contracts and enforcemento Data quality checks and validation ruleso Failure detection in CI pipelines (not post-deployment)<ul><li>Lead incident management and root cause analysis</li></ul>Data Governance &amp; Quality<ul><li>Establish data governance frameworks:</li></ul>o Standards, policies, and best practices<ul><li>Enforce:</li></ul>o Data integrityo Data lineage and traceabilityo Access controls and compliance<ul><li>Separate and maintain clear boundaries between:</li></ul>o Core governed datasetso Downstream analytics/BI layersCloud &amp; Big Data Integration<ul><li>Integrate systems with:</li></ul>o Data lakes and large-scale data platforms<ul><li>Work with modern cloud ecosystems (AWS preferred):</li></ul>oo Data warehouse platforms (e.g., Redshift, Snowflake)<ul><li>Design cost-efficient and scalable data solutions</li></ul>Analytics Engineering &amp; Data Products<ul><li>Design and deliver data products used by:</li></ul>o Analystso Data scientistso Product teams<ul><li>Build reusable frameworks for:</li></ul>o Data transformationo Orchestrationo Feature engineering (ML readiness)<ul><li>Support advanced analytics and reporting use cases</li></ul>CI/CD &amp; DevOps for Data<ul><li>Implement CI/CD pipelines for data workflows</li><li>Automate:</li></ul>o Testingo Deploymento Validation<ul><li>Use version control systems (Git/GitHub)</li><li>Ensure:</li></ul>o High availabilityo Backup and recovery strategiesProgramming &amp; Tooling<ul><li>Develop solutions using:</li></ul>oo Python (automation, validation, tooling)<ul><li>Work with tools such as:</li></ul>o dbt (deep experience required)o DBeaver, Visual Studioo Orchestration tools (e.g., Dagster or similar)Leadership &amp; Collaboration<ul><li>Lead cross-functional technical initiatives</li><li>Mentor and guide junior to mid-level data engineers</li><li>Conduct:</li></ul>o Code reviewso Architecture discussionso Knowledge sharing sessions<ul><li>Collaborate with:</li></ul>o Engineering teamso Product managerso Business stakeholders<ul><li>Translate business requirements into scalable data solutions</li></ul>Strategic Impact<ul><li>Drive platform evolution and innovation</li><li>Identify opportunities for:</li></ul>o Performance improvementso Cost optimization (FinOps mindset)o Automation and scalability<ul><li>Influence organizational data strategy and roadmapRequired Qualifications</li><li>Bachelor&rsquo;s degree in computer science, Engineering, IT, or related field</li><li>4&ndash;5+ years of experience in data engineering or analytics engineering</li><li>Strong expertise in:</li></ul>o Data modeling (star schema, dimensional modeling)o SQL and performance tuningo ETL/ELT pipeline development<ul><li>Hands-on experience with:</li></ul>o Data warehousing and data lakeso Big data integrations<ul><li>Experience with:</li></ul>o Cloud platforms (AWS preferred)o Data quality, validation, and governance frameworks<ul><li>Strong understanding of:</li></ul>o System designo Scalable architecture<ul><li>Excellent communication and stakeholder management skills</li><li>Ability to work in agile, fast-paced environments</li><li>Eligibility to obtain security clearance (if required)</li></ul>Preferred Qualifications<ul><li>Experience with:</li></ul>o AWS services (Glue, Lambda, etc.)o Snowflake, Redshifto dbt (production-level deployments)<ul><li>Knowledge of:</li></ul>o Machine learning data pipelineso Certifications:o SQL Server, CDMP, MCSA, or similar<ul><li>Experience in:</li></ul>o Healthcare, defense, or regulated industries<ul><li>Familiarity with:</li></ul>o CI/CD for data systemso Data governance and FinOps practicesWhat Makes a Strong Candidate<ul><li>Thinks of systems, not just pipelines</li><li>Focuses on root-cause solutions, not temporary fixes</li><li>Balances:</li></ul>o Business valueo Scalabilityo Maintainability<ul><li>Strong ownership mindset with ability to lead initiatives end-to-end</li><li>Passion for building resilient, high-quality data platforms</li></ul>Job Type: Full-timePay: Rs250,000.00 - Rs350,000.00 per monthWork Location: In person

Lead Data Engineer

About the RoleWe are seeking a highly skilled and experienced Senior / Lead Data Engineer to design, build, and maintain scalable, reliable, and high-performance data systems.In this role, you will take ownership of data platforms, lead cross-functional initiatives, and enable analytics, machine learning, and business intelligence across the organization. You will play a key role in shaping data architecture, ensuring data quality and governance, and supporting data-driven decision-making.Key ResponsibilitiesData Architecture &amp; Modeling<ul><li>Design and implement scalable data models (star schema, fact/dimension tables)</li><li>Develop conceptual, logical, and physical data models</li><li>Build enterprise data warehouse solutions with high performance and scalability</li><li>Define and enforce data modeling standards and best practices</li></ul>Data Engineering &amp; Pipeline Development<ul><li>Build and maintain end-to-end data pipelines (ingestion &rarr; transformation &rarr; serving)</li><li>Develop ETL/ELT processes using modern tools and frameworks</li><li>Implement data validation pipelines and staging layers</li><li>Optimize SQL queries, indexing, and database performance</li></ul>Data Platform Reliability &amp; Observability<ul><li>Ensure reliability and integrity of data pipelines</li><li>Build monitoring dashboards and alerting systems</li><li>Implement data quality checks and schema enforcement</li><li>Lead incident management and root cause analysis</li></ul>Data Governance &amp; Quality<ul><li>Establish data governance frameworks and policies</li><li>Ensure data integrity, lineage, and compliance</li><li>Manage access controls and data security</li><li>Maintain separation between core datasets and analytics layers</li></ul>Cloud &amp; Big Data Integration<ul><li>Integrate systems with data lakes and large-scale platforms</li><li>Work with cloud environments (AWS preferred)</li><li>Utilize tools such as AWS Glue, Lambda, Redshift, or Snowflake</li><li>Design scalable and cost-efficient data solutions</li></ul>Analytics Engineering &amp; Data Products<ul><li>Build and deliver data products for analysts and data scientists</li><li>Develop reusable frameworks for transformation and orchestration</li><li>Support advanced analytics and reporting</li></ul>CI/CD &amp; DevOps for Data<ul><li>Implement CI/CD pipelines for data workflows</li><li>Automate testing, deployment, and validation</li><li>Use version control tools (Git/GitHub)</li><li>Ensure high availability and disaster recovery</li></ul>Programming &amp; Tools<ul><li>Strong expertise in SQL (advanced level)</li><li>Proficiency in Python for automation and data processing</li><li>Experience with tools such as dbt, DBeaver, and orchestration tools (e.g., Dagster)</li></ul>Leadership &amp; Collaboration<ul><li>Lead technical initiatives and mentor junior engineers</li><li>Conduct code reviews and architecture discussions</li><li>Collaborate with engineering, product, and business teams</li><li>Translate business requirements into scalable data solutions</li></ul>Requirements<ul><li>Bachelor&rsquo;s degree in Computer Science, Engineering, IT, or related field</li><li>4&ndash;5+ years of experience in Data Engineering or related roles</li><li>Strong expertise in data modeling, SQL, and ETL/ELT pipelines</li><li>Experience with data warehousing and data lakes</li><li>Hands-on experience with cloud platforms (AWS preferred)</li><li>Strong understanding of system design and scalable architecture</li><li>Excellent communication and stakeholder management skills</li><li>Ability to work in fast-paced, agile environments</li></ul>Preferred Qualifications<ul><li>Experience with AWS services (Glue, Lambda, etc.)</li><li>Experience with Snowflake or Redshift</li><li>Strong hands-on experience with dbt</li><li>Knowledge of machine learning data pipelines</li><li>Certifications (SQL Server, CDMP, MCSA, or similar)</li><li>Experience in regulated industries (Healthcare, Defense, etc.)</li><li>Familiarity with CI/CD, data governance, and FinOps practices</li></ul>Job Type: Full-timePay: Rs250,000.00 - Rs400,000.00 per monthWork Location: In person

Senior Data Engineer

ACE Money Transfer

<div>About Us: 
 
We are a dynamic and fast-growing financial technology group headquartered in Manchester, United Kingdom, with an established presence across the UK, Europe, Canada, Australia, Pakistan, and Bangladesh. Our group, encompassing ACE Money Transfer and ACE Union, operates across two regulated verticals: Electronic Money Services (EMI) and Cross-Border Remittances. 
Through our digital platforms, including mobile apps, web portals, and APIs, we deliver a comprehensive range of regulated financial services. These include digital payments, e-wallets, electronic money issuance, prepaid cards, mobile top-ups, bill payments, and international money transfers, designed to serve both individual and business customers in over 100 countries. By leveraging cutting-edge technologies such as AI for fraud detection, automation for seamless transactions, and partnerships with global leaders like Mastercard, we provide secure, user-friendly, and accessible financial solutions that adapt to the evolving needs of a global customer base. 
As we scale our EMI and remittance operations amid 2025's fintech landscape marked by real-time payments, embedded finance, blockchain integration, and sustainability initiatives, we are building a leadership team to drive innovation, regulatory compliance, and excellence across our dual-regulated ecosystem. 
 
Job Overview:
 
 
This role is focused on designing and delivering scalable, secure, and high-performance data architectures to support the organization&rsquo;s expanding analytical and operational needs. The Senior Data Engineer will work closely with cross-functional teams to understand complex data requirements, define and implement robust data transformation rules, and lead the development and optimization of end-to-end data pipelines and data warehouse infrastructure. 
The ideal candidate will have hands-on experience in API based data integrations with third-party platforms, as well as a strong grasp of data governance principles. This includes implementing policies to ensure data quality, privacy, security, and compliance with regulatory standards. The role also involves optimizing workflows for cost efficiency and performance, while providing technical leadership to engineering and analytics teams in executing complex, data driven initiatives. 
 
Key Responsibilities:<ul><li>
Architecting Scalable Data Systems: Designing robust data infrastructures capable of supporting increasing data volume and complexity.</li><li>
Design Data Pipelines: Develop efficient data ingestion pipelines and ETL processes capable of handling both structured and unstructured data effectively.</li><li>
Data Warehouse Management: Manage and optimize the data warehouse, ensuring efficient data storage, retrieval, and transformation. Implement best practices for organizing and managing raw, processed, and curated data, with scalability and future growth in mind</li><li>
Optimize Data Modelling: Write, optimize, and maintain complex SQL queries and Python scripts to ensure efficient data processing.</li><li>
Streamlining Data Workflows: Enhancing data storage, processing, and access methods to improve efficiency, strengthen data observability, and reduce operational costs through targeted infrastructure optimizations.</li><li>
Governance &amp; Quality: Develop and maintain data quality checks to ensure data is accurate, consistent, and regulatory compliant.</li><li>
Develop Integration Procedures: Design and implement processes to integrate data warehouse solutions into operational IT environments.</li><li>
Driving Technical Leadership: Guiding engineering and analytics teams in the execution of data-driven initiatives and innovation.</li><li>
Research &amp; Development: Keep up with the latest technological trends and identify innovative solutions to address customer challenges and company priorities.</li></ul><div> 

Skills and Qualifications:<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Engineering, Computer Science, or a related field, or equivalent professional experience.</li><li>
Minimum of 4 years of hands-on experience in a Data Engineering or Data Architecture role.</li><li>
Proven experience with cloud platforms such as AWS, Azure, or GCP, with practical knowledge of their core data and infrastructure services.</li><li>
Proficient in using ETL tools and frameworks such as AWS Glue, Apache Airflow, Apache Spark, Kafka, Informatica, DataStage, or Talend for integrating data from multiple sources.</li><li>
Demonstrated expertise in setting up and managing scalable, high-performance data warehouse environments.</li><li>
Strong understanding of dimensional data modeling and mapping techniques, including Star, Snowflake, and Galaxy schemas.</li><li>
Solid understanding of data privacy regulations, including GDPR, and experience applying best practices for data security, compliance, and governance.</li><li>
Working knowledge of data observability principles and the full data lifecycle management.</li><li>
Extensive experience in designing and developing ETL architectures to support large-scale, distributed data processing.</li><li>
Deep knowledge of relational database concepts and advanced proficiency in SQL and Python for data manipulation and transformation.</li><li>
Experience working in distributed environments, including clustering, partitioning, and sharding strategies.</li><li>
Familiarity with building semantic models and preparing reporting and mapping documentation.</li><li>
Strong analytical and problem-solving skills, with a logical and solution-oriented mindset.</li><li>
Prior experience in the financial services sector is a plus.</li></ul></div>
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ACE Union

About Us:We are a dynamic and fast-growing financial technology group headquartered in Manchester, United Kingdom, with an established presence across the UK, Europe, Canada, Australia, Pakistan, and Bangladesh. Our group, encompassing ACE Money Transfer and ACE Union, operates across two regulated verticals: Electronic Money Services (EMI) and Cross-Border Remittances.Through our digital platforms, including mobile apps, web portals, and APIs, we deliver a comprehensive range of regulated financial services. These include digital payments, e-wallets, electronic money issuance, prepaid cards, mobile top-ups, bill payments, and international money transfers, designed to serve both individual and business customers in over 100 countries. By leveraging cutting-edge technologies such as AI for fraud detection, automation for seamless transactions, and partnerships with global leaders like Mastercard, we provide secure, user-friendly, and accessible financial solutions that adapt to the evolving needs of a global customer base.As we scale our EMI and remittance operations amid 2025's fintech landscape, marked by real-time payments, embedded finance, blockchain integration, and sustainability initiatives, we are building a leadership team to drive innovation, regulatory compliance, and excellence across our dual-regulated ecosystem.Job Overview: This role is focused on designing and delivering scalable, secure, and high-performance data architectures to support the organization&rsquo;s expanding analytical and operational needs. The Senior Data Engineer will work closely with cross-functional teams to understand complex data requirements, define and implement robust data transformation rules, and lead the development and optimization of end-to-end data pipelines and data warehouse infrastructure. The ideal candidate will have hands-on experience in API based data integrations with third-party platforms, as well as a strong grasp of data governance principles. This includes implementing policies to ensure data quality, privacy, security, and compliance with regulatory standards. The role also involves optimizing workflows for cost efficiency and performance, while providing technical leadership to engineering and analytics teams in executing complex, data driven initiatives.Key Responsibilities:<ul><li>Architecting Scalable Data Systems: Designing robust data infrastructures capable of supporting increasing data volume and complexity.</li><li>Design Data Pipelines: Develop efficient data ingestion pipelines and ETL processes capable of handling both structured and unstructured data effectively.</li><li>Data Warehouse Management: Manage and optimize the data warehouse, ensuring efficient data storage, retrieval, and transformation. Implement best practices for organizing and managing raw, processed, and curated data, with scalability and future growth in mind</li><li>Optimize Data Modelling: Write, optimize, and maintain complex SQL queries and Python scripts to ensure efficient data processing.</li><li>Streamlining Data Workflows: Enhancing data storage, processing, and access methods to improve efficiency, strengthen data observability, and reduce operational costs through targeted infrastructure optimizations.</li><li>Governance &amp; Quality: Develop and maintain data quality checks to ensure data is accurate, consistent, and regulatory compliant.</li><li>Develop Integration Procedures: Design and implement processes to integrate data warehouse solutions into operational IT environments.</li><li>Driving Technical Leadership: Guiding engineering and analytics teams in the execution of data-driven initiatives and innovation.</li><li>Research &amp; Development: Keep up with the latest technological trends and identify innovative solutions to address customer challenges and company priorities.</li></ul>Skills and Qualifications:<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Engineering, Computer Science, or a related field, or equivalent professional experience.</li><li>Minimum of 4 years of hands-on experience in a Data Engineering or Data Architecture role.</li><li>Proven experience with cloud platforms such as AWS, Azure, or GCP, with practical knowledge of their core data and infrastructure services.</li><li>Proficient in using ETL tools and frameworks such as AWS Glue, Apache Airflow, Apache Spark, Kafka, Informatica, DataStage, or Talend for integrating data from multiple sources.</li><li>Demonstrated expertise in setting up and managing scalable, high-performance data warehouse environments.</li><li>Strong understanding of dimensional data modeling and mapping techniques, including Star, Snowflake, and Galaxy schemas.</li><li>Solid understanding of data privacy regulations, including GDPR, and experience applying best practices for data security, compliance, and governance.</li><li>Working knowledge of data observability principles and the full data lifecycle management.</li><li>Extensive experience in designing and developing ETL architectures to support large-scale, distributed data processing.</li><li>Deep knowledge of relational database concepts and advanced proficiency in SQL and Python for data manipulation and transformation.</li><li>Experience working in distributed environments, including clustering, partitioning, and sharding strategies.</li><li>Familiarity with building semantic models and preparing reporting and mapping documentation.</li><li>Strong analytical and problem-solving skills, with a logical and solution-oriented mindset.</li><li>Prior experience in the financial services sector is a plus.</li></ul>Job Type: Full-timePay: Rs300,000.00 - Rs350,000.00 per monthApplication Question(s):<ul><li>The shift timing connected with the role is 01:00 PM PST to 10:00 PM PST. Is it feasible for you to work in these timings?</li><li>Is it possible for you to commute daily to Gulberg-3 Lahore, or to relocate to Lahore city for this job?</li><li>What is your current salary package?</li><li>What is your expected salary?</li></ul>Experience:<ul><li>Data Engineering or Data Architecture: 4 years (Required)</li></ul>Language:<ul><li>English proficiently (Required)</li></ul>Work Location: In person

Polarity Holdings

Starting Salary: Rs 501,000 PKR / monthSchedule: U.S. Eastern, Monday through FridayLocation: 100% Remote, Full-TimeAbout the RoleFalcon Scaling and PolarityIQ build private capital markets intelligence products. Our clients are family offices, institutional LPs, fund managers, investment banks, and registered investment advisors. They pay premium prices for verified, decision-maker-level intelligence on capital allocators worldwide.We operate a commercially active library of more than two hundred data products spanning family offices, institutional investors, venture capital, private equity, fund of funds, mutual funds, real estate, and high net worth individuals. Our flagship products include Family Office MAX (25,000+ executives across 10,000+ family offices) and LP MAX Bundle (80,000+ contacts across 17,000+ institutional LPs representing over $2 trillion in AUM).The Senior Data Engineer (Full Chain Builder) owns Project NOVA: the three-stage production pipeline that acquires records at scale, enriches them to the granularity capital allocators will pay for, and activates them inside PolarityIQ through agentic retrieval that surfaces signals autonomously.This is hands-on, high-autonomy work. You will build original scraping pipelines, architect multi-provider enrichment waterfalls, deploy production RAG systems, and build the agentic retrieval layer across our intelligence library. You ship products paying customers rely on, not internal demos.Before You ApplyIf your resume does not name a specific client, a real user volume, and what breaks when your system goes down: do not apply.If you have not deployed at least one production RAG system that a non-technical user relied on: do not apply.If Claude Code is not already part of your daily workflow, this role will move too fast for you.CompensationStarting salary is Rs 501,000 PKR per month. The role includes a revenue-sharing component tied directly to your contributions. You are paid weekly, on time.Strong performers regularly see total earnings scale meaningfully within the first four to eight weeks, with continued upside as contributions compound. On-target monthly earnings can exceed Rs 1,000,000 PKR within six to eight months.How You Enter &mdash; The 30-Day SprintThis role begins with a paid, deliverable-based 30-Day Build and Monetization Sprint at Rs 501,000 per month. You do not need to leave your current position. You operate on your own schedule, deploy existing products against real demand, and report what happens when your work meets the market.This is not a trial period. It is a real operating environment. At day 31, both sides hold 30 days of evidence. You will know whether the earnings trajectory and autonomy are real. We will know how you operate under real conditions.What You'll OwnAcquire &mdash; Sourcing and Scraping<ul><li>Build scraping pipelines against family office sites, regulatory filings, SEC EDGAR, state corporate registration databases, and professional networks.</li><li>Handle production anti-bot environments &mdash; Cloudflare, DataDome, PerimeterX &mdash; through residential proxies, CAPTCHA solvers, and stealth browser configurations.</li><li>Orchestrate recurring scraping with Apache Airflow, Prefect, or equivalent. Scheduled, monitored, recoverable.</li><li>Validate sourced records against schema contracts using Pydantic or equivalent. Every record passes the validation gate before entering the pipeline.</li></ul>Enrich &mdash; Multi-Provider Waterfalls<ul><li>Build and manage multi-source enrichment waterfalls using Clay.com, Apollo, Hunter, People Data Labs, Clearbit, and similar platforms.</li><li>Know the cost, coverage, and reliability tradeoffs between providers field by field. Build waterfalls that minimize cost while maximizing coverage.</li><li>Add granularity dimensions that matter: decision-maker layer, investment thesis, activity signals, relationship graph, structural classification, validation metadata.</li><li>Apply data hygiene principles across all pipelines: bounce rates, email verification, contact scoring, stale record detection.</li><li>Operate orchestration tooling that lets enrichment chains run end-to-end without manual stitching: n8n, Apache Airflow, Prefect, Make, or equivalent. The waterfall is one workflow, not a sequence of disconnected scripts.</li><li>Build cost-efficient pipelines that scale without proportional cost growth.</li></ul>Activate &mdash; Agentic RAG and RetrievalPolarityIQ's core intelligence layer is built on RAG. This is not experimental. It is the foundation of how our platform transforms raw family office data into queryable, actionable intelligence.<ul><li>Architect end-to-end RAG systems: document ingestion, chunking strategy, embedding model selection, vector database architecture, retrieval pipeline design.</li><li>Select and justify vector database choices (ChromaDB, Pinecone, Supabase pgvector, Weaviate, or equivalent) based on cost, latency, and scale requirements.</li><li>Implement hybrid retrieval strategies combining semantic vector search with keyword matching (BM25) for higher relevance and accuracy.</li><li>Build retrieval evaluation loops. Assess whether your system returns accurate, grounded results and diagnose when it does not.</li><li>Design and deploy autonomous AI agents using LangChain, CrewAI, or equivalent frameworks. Agents that gather, validate, and synthesize intelligence across data sources.</li><li>Integrate agentic workflows into the PolarityIQ platform so users receive signal delivery, not just search results.</li></ul>Database Architecture<ul><li>Own the architecture, integrity, and growth of PolarityIQ's core intelligence database.</li><li>Design and manage relational schema across Supabase/PostgreSQL, ensuring normalization, indexing, and query performance at scale.</li></ul>Technical StackScraping and AcquisitionScrapy, Playwright, curl_cffi, BeautifulSoup, Requests. Apify, Phantombuster, Browse AI at production scale. Anti-bot fluency: Cloudflare, DataDome, PerimeterX (named experience, not theoretical). Proxies: Bright Data, Oxylabs, Zyte, Smartproxy. CAPTCHA solvers: 2Captcha, Anti-Captcha, CapSolver. Orchestration: Apache Airflow, Prefect, AWS Lambda.EnrichmentClay.com as primary environment: tables, waterfalls, formulas, AI columns. Provider depth: Apollo, Hunter, People Data Labs, Clearbit, BetterContact, Cognism. Validation: Pydantic, Pandera, or Great Expectations applied to scraping output.RAG and Agentic SystemsProduction RAG deployment covering document ingestion, chunking, embeddings, hybrid retrieval, re-ranking, grounding. Vector databases: ChromaDB, Pinecone, Supabase pgvector, Weaviate. Agent frameworks: LangChain, CrewAI, LlamaIndex. LLM APIs: OpenAI, Anthropic Claude, Gemini, with understanding of cost, latency, and reliability tradeoffs.Claude Code &mdash; Non-NegotiableYou operate Claude Code in terminal-based, agentic workflows. Not as a code completer but as a development collaborator you direct, correct, and build with autonomously. You know its limits and call them without hand-holding.Development and InfrastructureBackend with Python, Node.js, or similar. SQL, relational schema design, query optimization. Managed platforms (Supabase, PostgreSQL). API integration (REST, GraphQL, webhooks). Git / GitHub.Who You AreThe technical skills matter. This section matters more.You take ownership before being asked. You measure yourself by outcomes, not activity. You are honest, even when it is uncomfortable. You are reliable, not occasionally but consistently. You are resourceful enough to treat every dollar spent like it is coming out of your own pocket.Your thought process is disciplined. You verify before you assert. You distinguish between facts, inferences, and conclusions, and you never conflate them. You test your assumptions before acting. You are willing to challenge your own hypotheses when the evidence points elsewhere.You use AI extensively but think independently first. Claude Code feels like a natural extension of how you work. You know when it is wrong, when it is shallow, and when to apply the human layer of judgment no prompt can replicate.You communicate in flawless English. Your first draft should be publishable. You do not require heavy editing cycles.Job Type: Full-timePay: Rs501,000.00 per monthEducation:<ul><li>Master's (Preferred)</li></ul>Language:<ul><li>English (Preferred)</li></ul>Work Location: In person

ByteCrew

<div>
 
 Role Summary
 
 
 
 About the job Data Engineer
 
 
 We are seeking a Data Engineer to design, build, and operate data pipelines and warehouses powering
 
 
 enterprise analytics and reporting. The role covers ingestion, transformation, modelling, and operationalisation
 
 
 across cloud and on-prem data sources.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and implement batch + streaming data pipelines (ETL/ELT).
 </li>
 <li>
 Build and maintain dimensional/data-warehouse models (Star/Snowflake schema, slowly-changing
 
 
 </li>
 </ul>
 dimensions).
 
 
 <ul>
 <li>
 Develop in SQL, Python, and at least one orchestrator (Airflow, Azure Data Factory, AWS Glue).
 </li>
 <li>
 Operate data quality checks, lineage, and observability (Great Expectations, Monte Carlo, or similar).
 </li>
 <li>
 Optimise warehouse performance (Snowflake, Synapse, BigQuery, Redshift).
 </li>
 <li>
 Partner with BI/analytics teams on semantic models and self-service consumption.
 </li>
 <li>
 Document pipelines, schemas, and runbooks.
 
 
 </li>
 </ul>
 
 Required Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in CS, Engineering, Statistics, or equivalent.
 </li>
 <li>
 4+ years building production data pipelines.
 </li>
 <li>
 Strong SQL (window functions, CTEs, query tuning) and Python.
 </li>
 <li>
 Hands-on with at least one major DW/Lakehouse: Snowflake, BigQuery, Synapse, Redshift, Databricks.
 </li>
 <li>
 Experience with at least one orchestrator: Airflow, ADF, Glue, dbt + scheduler.
 </li>
 <li>
 Familiarity with cloud object storage (S3, ADLS, GCS) and file formats (Parquet, ORC, Avro).
 </li>
 <li>
 Professional English &mdash; mandatory.
 
 
 </li>
 </ul>
 
 Preferred / Nice To Have
 
 
 
 <ul>
 <li>
 Working knowledge of Arabic is a plus.
 </li>
 <li>
 Streaming experience: Kafka, Kinesis, Event Hubs, Spark Structured Streaming.
 </li>
 <li>
 dbt Analytics Engineer or cloud data engineer certifications.
 </li>
 <li>
 Exposure to data governance/cataloguing (Purview, Unity Catalog, Collibra).
 </li>
 </ul>
</div>

Data Engineer
Lahore, Pakistan

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Data Engineer Lahore, Pakistan